Performance Characterization of Multifunctional Wings With Integrated Solar Cells for Unmanned Air Vehicles

Gupta

2017

Biologically-inspired flapping wing flight is attractive at low Reynolds numbers and at high angles of attack, where fixed wing flight performance declines precipitously. While the merits of flapping propulsion have been intensely investigated, enhancing flapping propulsion has proven challenging because of hardware constraints and the complexity of the design space. For example, increasing the size of wings generates aerodynamic forces that exceed the limits of actuators used to drive the wings, reducing flapping amplitude at higher frequencies and causing thrust to taper off. Therefore, augmentation of aerodynamic force production from alternative propulsion modes can potentially enhance biologicallyinspired flight. In this paper, we explore the use of auxiliary propellers on Robo Raven, an existing flapping wing air vehicle (FWAV), to augment thrust without altering wing design or flapping mechanics. Designing such a platform poses two major challenges. First, potential for negative interaction between the flapping and propeller airflow reducing thrust generation. Second, adding propellers to an existing platform increases platform weight and requires additional power from heavier energy sources for comparable flight time. In this paper, three major findings are reported addressing these challenges. First, locating the propellers behind the flapping wings (i.e. in the wake) exhibits minimal coupling without positional sensitivity for the propeller placement at or below the platform centerline. Second, the additional thrust generated by the platform does increase aerodynamic lift. Third, the increase in aerodynamic lift offsets the higher weight of the platform, significantly improving payload capacity. The effect of varying operational payload and flight time for different mixed mode operating conditions was predicted, and the trade-off between the operational payload and operating conditions for mixed mode propulsion was characterized. Flight tests revealed the improved agility of the platform when used with static placement of the wings for various aerobatic maneuvers, such as gliding, diving, or loops.

Section: Testing Methodologymentioning

confidence: 99%

Characterizing and modeling the enhancement of lift and payload capacity resulting from thrust augmentation in a propeller-assisted flapping wing air vehicle

Holness

Gupta

2017

“…This modified design was used to characterize Robo Raven in previous works. 18,21,22,73 The test stand was equipped with the same model of servos used in flight, Futaba high-speed and high-torque actuators. The servos motors were powered by a DC power supply with motor control signal provided by an Arduino Nano, and the same microcontroller used in flight.…”

Section: Configuration Of Solar Cells In Wings and Wind Tunnel Measurmentioning

confidence: 99%

“…[14][15][16][17] A number of bio-inspired flapping wing air vehicles (FWAVs) have been developed in pursuit of desirable flight characteristics, including research platforms exploring warping wing flight and University of Maryland's Robo Raven series. 9,[18][19][20][21][22][23][24][25][26][27][28][29][30][31] As a means of reducing system complexity and weight, many successful flapping wing platforms rely on a single actuator [32][33][34] to drive one degree of freedom while other degrees of freedom are generated using passive means to achieve complex kinematics. 9,13,27,[34][35][36][37][38][39][40] One such approach is the usage of flexible membranes mylar, latex, or fabric, which passively deform and are lightweight.…”

Section: Introductionmentioning

confidence: 99%

A design framework for realizing multifunctional wings for flapping wing air vehicles using solar cells

Holness

Solheim

et al. 2019

Long flight durations are highly desirable to expand mission capabilities for unmanned air systems and autonomous applications in particular. Flapping wing aerial vehicles are unmanned air system platforms offering several performance advantages over fixed wing and rotorcraft platforms, but are unable to reach comparable flight times when powered by batteries. One solution to this problem has been to integrate energy harvesting technologies in components, such as wings. To this end, a framework for designing flapping wing aerial vehicle using multifunctional wings using solar cells is described. This framework consists of: (1) modeling solar energy harvesting while flying, (2) determining the number of solar cells that meet flight power requirements, and (3) determining appropriate locations to accommodate the desired number of solar cells. A system model for flapping flight was also developed to predict payload capacity for carrying batteries to provide energy only for power spikes and to enable time-to-land safely in an area where batteries can recharge when the sun sets. The design framework was applied to a case study using flexible high-efficiency (>24%) solar cells on a flapping wing aerial vehicle platform, known as Robo Raven IIIv5, with the caveat that a powertrain with 81% efficiency is used in place of the current servos. A key finding was the fraction of solar flux incident on the wings during flapping was 0.63 at the lowest solar altitude. Using a 1.25 safety factor, the lowest value for the purposes of design will be 0.51. Wind tunnel measurements and aerodynamic modeling of the platform determined integrating solar cells in the wings resulted in a loss of thrust and greater drag, but the resulting payload capacity was unaffected because of a higher lift coefficient. A time-to-land of 2500 s was predicted, and the flight capability of the platform was validated in a netted test facility.

“…23 As a consequence of these research efforts, we have developed the Robo Raven FWAV, 5 which has since become a testbed for additional research in related fields. [24][25][26][27] Historically, the development of the Robo Raven platform has relied on a significant amount of experimental evaluation to establish feasible conditions for flight. This approach has resulted in a body of data that describes the flight envelope and subsystem parameters that lead to acceptable operation, but is a time-consuming strategy for exploring component interactions due to reliance on a huge number of experimental trials.…”

Section: Introductionmentioning

confidence: 99%

A simulation-based approach to modeling component interactions during design of flapping wing aerial vehicles

Gerdes

Gupta

2019

A new flapping wing aerial vehicle (FWAV) simulation methodology is presented that combines models of the key subsystems: (1) the actuator, (2) the battery, and (3) the wings. This approach captures component interactions that are inherently coupled in order to realize system-level designs for optimal system performance. The approach demonstrates that coupling between wing sizing, flapping motions, and loading conditions propagate into the motor–battery model to alter system-level performance properties. For the actuator subsystem model, a generalized servo motor using empirically derived coefficients to describe torque and angular velocity bandwidth in terms of voltage and current. This model is coupled with a lithium polymer battery model accounting for the nonlinear voltage drop and capacity derating effects associated with loading conditions. For aerodynamic predictions of the wing subsystem, a blade element model for predicting aerodynamic forces is coupled with an elastic wing deformation model that accounts for bending and twisting of the blade elements. System-level performance is then modeled in a design case study by coupling all of the subsystem models to account for relevant interactions, which generates a design trade space spanning a range of wing sizes, airspeeds, and flapping condition. The results from the simulation offer insight into vehicle configuration settings that provide maximum performance in terms of lift and endurance for the Robo Raven II flapping wing aerial vehicle. Experimental validation of the modeling approach shows good predictive accuracy. In addition, the presented framework offers a generalized approach for coupling interacting subsystems to improve overall predictive accuracy and identify areas where component-level improvements may offer system-level performance gains.